Consistent follow-up segmentation of pleural thickenings

Pleural thickenings, which are an indicator for pleural mesothelioma, can be detected and analyzed using thoracic CT-data. They may cover a large area on the pleura surface and can have complex morphologies. Image noise, small deformations and especially the unclear boundary can significantly influence the segmentation process. Two independent segmentations from two points in time might independently suffer from these influences. As a consequence, they cannot be combined for reliable growth rate estimation. Therefore, we suggest a method to introduce consistency between both points in time. The method is carefully designed to estimate small growth from low resolution structures with complex morphologies. First, a surface mesh with segmentation confidence is extracted from one point in time. This mesh is refined considering the segmentation confidence and partial volume. Subsequently, this refined mesh is transferred to the other point in time and growth is tracked with sub-voxel precision.